Introduce me to UR

• This is my first semester at UR!
  • If you want to learn more about where I’m coming from: https://fredner.org
• How would you describe the culture of UR?
  • Discuss with the people next to you.

Anonymous survey

Please complete this brief anonymous survey: https://richmond.ca1.qualtrics.com/jfe/form/SV_8vsOr6mRZGypJVc

This link was included with the announcement you received on Sunday.

I will use the survey results to design the class.

What do we mean by “data science?”

• We will learn and practice a series of methods for organizing, collecting, visualizing, manipulating, and exploring different kinds of data.
• We focus on the creation of data and application of methods, not theoretical or foundational questions.
• This is not a mathematics course, nor will it resemble a traditional introductory statistics class. We will spend the entire semester writing code to apply data science concepts.

Why do data science? One perspective:

• There is too much information in the world.
  • e.g., every minute, approximately 500 hours of video are uploaded to YouTube.
• People value useful information and new knowledge.
  • Almost none of those 500 hours are worth your finite time.
• Data science transforms data into useful information.

How do people do data science?

• R and Python are the two most popular programming languages for data science.
• We will be using R in this class.
• However, the main learning goal of this class is not R.
• The main learning goal is to understand:
  • what good data is
  • how to ask good questions of data
  • how we can use good data to answer good questions

What does the data science process look like?

flowchart LR
    A[Import] --> B[Tidy]
    B --> C[Transform]
    subgraph Understand
        direction LR
        C --> D[Visualize]
        D --> E[Model]
        E --> C
    end
    Understand --> F[Communicate]
    subgraph Program
        direction LR
        A
        B
        Understand
        F
    end

from R for Data Science (2023)

An effective example

Questions about syllabus?

The elephant in the room

• No one knows the best course of action for students or professors regarding GenAI (e.g., ChatGPT).
• As a result, you will probably get different instructions from all of your professors about it.
• Use of GenAI is not required in this course.
• But it is already widespread in all domains of programming, including data science, so it is not prohibited either.

Step 1: R

Install the version for your operating system: https://cloud.r-project.org

If you already have R installed, install the newest version.

If you have a Mac that was made in 2020 or later, choose “Apple Silicon.”

Step 2: RStudio

Install the free version of RStudio Desktop: https://posit.co/downloads/

If you already have RStudio installed, install the newest version.

Step 4: Install the tidyverse

Type the following in the console:

install.packages("tidyverse")

A bunch of things should happen.

You only need to let me know if you get an Error.

Step 4.5: Debugging

• If you ran into a problem during the installation, raise your hand.
• If you finished installing everything successfully and think you can help others, go to the closest person with their hand up.

Step 5: Download materials

• Go to Blackboard / Course Documents / 00 - Intro
• Download DSST289.zip
• Extract this .zip file
• Move it to a location on your computer that you can find easily (e.g., Desktop)